package algorithm

import (
	"time"
)

// HeuristicSolver 启发式规则求解器
type HeuristicSolver struct {
	Rules []HeuristicRule
}

// HeuristicRule 启发式规则接口
type HeuristicRule interface {
	Apply(state *State) *Action
	Priority() int
}

// TimeWindowRule 时间窗口规则
type TimeWindowRule struct {
	WindowSize time.Duration
}

// LocationClusterRule 地理位置聚类规则
type LocationClusterRule struct {
	MaxClusterSize int
	MaxDistance    float64
}

// VehicleCapacityRule 车辆容量规则
type VehicleCapacityRule struct {
	MinUtilization float64
}

// NewHeuristicSolver 创建新的启发式规则求解器
func NewHeuristicSolver() *HeuristicSolver {
	return &HeuristicSolver{
		Rules: []HeuristicRule{
			&TimeWindowRule{
				WindowSize: 30 * time.Minute,
			},
			&LocationClusterRule{
				MaxClusterSize: 10,
				MaxDistance:    5.0, // 公里
			},
			&VehicleCapacityRule{
				MinUtilization: 0.8,
			},
		},
	}
}

// Solve 使用启发式规则求解
func (s *HeuristicSolver) Solve(state *State) []*Action {
	var actions []*Action
	currentState := state

	for len(currentState.PendingOrders) > 0 {
		var bestAction *Action
		bestPriority := -1

		// 应用所有规则，选择优先级最高的动作
		for _, rule := range s.Rules {
			action := rule.Apply(currentState)
			if action != nil && rule.Priority() > bestPriority {
				bestAction = action
				bestPriority = rule.Priority()
			}
		}

		if bestAction == nil {
			break
		}

		actions = append(actions, bestAction)
		currentState = s.applyAction(currentState, bestAction)
	}

	return actions
}

// applyAction 应用动作到状态
func (s *HeuristicSolver) applyAction(state *State, action *Action) *State {
	// TODO: 实现状态更新逻辑
	return state
}

// Apply 实现TimeWindowRule的Apply方法
func (r *TimeWindowRule) Apply(state *State) *Action {
	// TODO: 实现时间窗口规则
	return nil
}

// Priority 实现TimeWindowRule的Priority方法
func (r *TimeWindowRule) Priority() int {
	return 1
}

// Apply 实现LocationClusterRule的Apply方法
func (r *LocationClusterRule) Apply(state *State) *Action {
	// TODO: 实现地理位置聚类规则
	return nil
}

// Priority 实现LocationClusterRule的Priority方法
func (r *LocationClusterRule) Priority() int {
	return 2
}

// Apply 实现VehicleCapacityRule的Apply方法
func (r *VehicleCapacityRule) Apply(state *State) *Action {
	// TODO: 实现车辆容量规则
	return nil
}

// Priority 实现VehicleCapacityRule的Priority方法
func (r *VehicleCapacityRule) Priority() int {
	return 3
}

// CalculateCost 计算决策成本
func (s *HeuristicSolver) CalculateCost(action *Action) *Cost {
	// TODO: 实现成本计算
	return &Cost{
		Distance:     0,
		Time:         0,
		VehicleUsage: 0,
		OrderDelay:   0,
	}
}
